Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions

Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions

Quantum computing is envisaged as an evolving paradigm for solving computationally complex optimization problems with a large-number factorization and exhaustive search. Recently, there has been a proliferating growth of the size of multi-dimensional datasets, the input-output space dimensionality,...

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Bibliographic Details
Main Authors: Trung Q. Duong, James Adu Ansere, Bhaskara Narottama, Vishal Sharma, Octavia A. Dobre, Hyundong Shin
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Open Journal of Vehicular Technology
Subjects:
6G networks
machine learning
quantum machine learning
quantum security
Online Access:https://ieeexplore.ieee.org/document/9870532/

Internet

https://ieeexplore.ieee.org/document/9870532/

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